Package: mogsa 1.39.0

Chen Meng

mogsa: Multiple omics data integrative clustering and gene set analysis

This package provide a method for doing gene set analysis based on multiple omics data.

Authors:Chen Meng

mogsa_1.39.0.tar.gz
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mogsa.pdf |mogsa.html
mogsa/json (API)
NEWS

# Install 'mogsa' in R:
install.packages('mogsa', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:
  • NCI60_4array_supdata - Supp data for Microarray gene expression profiles of the NCI 60 cell lines from 4 different platforms
  • NCI60_4arrays - Microarray gene expression profiles of the NCI 60 cell lines from 4 different platforms

On BioConductor:mogsa-1.39.0(bioc 3.20)mogsa-1.38.0(bioc 3.19)

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

bioconductor-package

29 exports 0.91 score 61 dependencies 1 mentions

Last updated 2 months agofrom:f4d1b5d15a

Exports:annotate.gsbootMbpcabootMoabox.gs.featurecombinedecompose.gs.groupdecompose.gs.inddistMoagetmgsaGISmatpowermbpcamoamoaCoefmoaScoremoGapmogsapairwise.rvplotplotGSprepGraphiteprepMsigDBprepSupMoaprintshowsoftKsummarysup.moawsvd

Dependencies:annotateAnnotationDbiaskpassBiobaseBiocGenericsBiostringsbitbit64bitopsblobcachemcaToolscliclustercorpcorcpp11crayoncurlDBIfastmapgenefilterGenomeInfoDbGenomeInfoDbDatagluegplotsgraphgraphiteGSEABasegtoolshttrIRangesjsonliteKEGGRESTKernSmoothlatticelifecyclemagrittrMatrixMatrixGenericsmatrixStatsmemoisemimeopensslpkgconfigplogrpngpurrrR6rappdirsrlangRSQLiteS4VectorssurvivalsvdsysUCSC.utilsvctrsXMLxtableXVectorzlibbioc

moCluster: Integrative clustering using multiple omics data

Rendered frommoCluster-knitr.Rnwusingknitr::knitron Jun 30 2024.

Last update: 2019-05-07
Started: 2019-05-07

mogsa: gene set analysis on multiple omics data

Rendered frommogsa-knitr.Rnwusingknitr::knitron Jun 30 2024.

Last update: 2019-05-07
Started: 2019-05-07

Readme and manuals

Help Manual

Help pageTopics
Multiple omics clustering and gene set analysismogsa-package
Summary annotation information of a gene setannotate.gs
NIPALS algorithm with soft thresholding operator on rows and columnsbiSoftK
Bootstrap mbpca to estimate the coherence of different data setsbootMbpca
An internal function called by 'bootMbpca'.bootMbpcaK
Significant components in "moa" returned by function "moa".bootMoa
boxplot of gene set variables across all samples.box.gs.feature
Combine two objects of class 'mgsa' into one.combine combine,mgsa,mgsa-method combine-methods
Data-wise or PC-wise decomposition of gene set scores for all observations.decompose.gs.group
Data-wise or PC-wise decomposition of gene set scores for a single observation.decompose.gs.ind
deflat function used by 'mbpca'deflat
Calculate the distance matrix from an object of class 'moa-class'.distMoa
get values in an object of class "mgsa".getmgsa
calculate gene influential scores of genes in a gene set.GIS
compute the power of a matrixmatpower
Extension of PCA to analyze multiple data setsmbpca
Class '"mgsa"'mgsa-class
Multiple omics data analysis using MFA or STATISmoa
Class '"moa"'moa-class plot,moa,missing-method
Class '"moa.sup"'moa.sup-class
Extract the loadings/coefficients from an object of class 'moa-class'.moaCoef
Extract global scores from an object of class 'moa-class'.moaScore
Gap statistic for clustering latent variables in 'moa-class'.moGap
multiple omics data integration and gene set analysismogsa
SVD based algorithm to calculate block Score and global scores for 'mbpca'.msvd
supp data for Microarray gene expression profiles of the NCI 60 cell lines from 4 different platformsNCI60_4array_supdata
Microarray gene expression profiles of the NCI 60 cell lines from 4 different platformsNCI60_4arrays
NIPALS algorithm with soft thresholding operatornipalsSoftK
pairwise RV coefficients.pairwise.rv
Methods for function 'plot'plot-methods
Plot the gene set spaceplotGS
Prepare pathway gene sets from graphite packageprepGraphite
Conver gmt format file to a listprepMsigDB
Prepare sumpplementary tables for projection by sup.moa or mogsa.prepSupMoa
Methods for function 'print'print print,mgsa-method print,moa-method print,moa.sup-method print-methods
preprocessing of input data in 'mbpca'.processOpt
Methods for function 'show'show show,mgsa-method show,moa-method show,moa.sup-method show-methods
Soft-thresholding operatorsoftK
Methods for function 'summary'summary summary,mgsa-method summary,moa-method summary,moa.sup-method summary-methods
Projecting supplementary tables on object of class 'moa-class'.sup.moa
convert 'mbpca' result to 'moa-class'toMoa
Weighted singular value decomposition (SVD)wsvd